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bioc_sc

WDL pipeline for standard Bioconductor/OSCA single-cell RNA-seq post-processing: load matrix, QC filter, normalize, select highly variable genes, run dimensionality reduction, cluster, identify marker genes, and annotate cell types
WDL Version
1.0
Nested Inputs Not Allowed
RUN WITH

sprocket run --target bioc_sc ww-bioc-sc.wdlww-bioc-sc.wdl [INPUTS]...

author
name
Taylor Firman
email
tfirman@fredhutch.org
url
https://raw.githubusercontent.com/getwilds/wilds-wdl-library/refs/heads/main/pipelines/ww-bioc-sc/ww-bioc-sc.wdl

Inputs

Required Inputs

Name
Type
Description
samples
Array[SingleCellSample]
List of single-cell sample objects, each with a name and either a pre-filtered 1...
List of single-cell sample objects, each with a name and either a pre-filtered 10x feature-barcode matrix (h5_matrix) or a raw, unfiltered one (raw_h5_matrix). Exactly one of the two must be provided per sample; if raw_h5_matrix is given, real cells are called with emptyDrops before QC

Other Inputs

Name
Type
Default
Description
mito_pattern
String
"^MT-"
Regex pattern identifying mitochondrial gene symbols, passed to ww-scran
Regex pattern identifying mitochondrial gene symbols, passed to ww-scran
"^MT-"
nmads
Float
3.0
Number of median absolute deviations from the median used to flag low-quality cells, passed to ww-scran
Number of median absolute deviations from the median used to flag low-quality cells, passed to ww-scran
3.0
n_hvgs
Int
2000
Number of top highly variable genes to select in ww-scran and use for PCA in ww-scater
Number of top highly variable genes to select in ww-scran and use for PCA in ww-scater
2000
n_pcs
Int
50
Number of principal components to compute in ww-scater
Number of principal components to compute in ww-scater
50
reference_dataset
String
"HumanPrimaryCellAtlasData"
Name of the celldex reference dataset function to fetch for cell-type annotation, passed to ww-singler
Name of the celldex reference dataset function to fetch for cell-type annotation, passed to ww-singler
"HumanPrimaryCellAtlasData"
reference_ensembl
Boolean
true
Fetch the celldex reference with Ensembl gene IDs instead of gene symbols, passed to ww-singler
Fetch the celldex reference with Ensembl gene IDs instead of gene symbols, passed to ww-singler
true
label_column
String
"label.main"
Column name in the reference object's colData containing cell-type labels, passed to ww-singler
Column name in the reference object's colData containing cell-type labels, passed to ww-singler
"label.main"
cpu_cores
Int
2
Number of CPU cores allocated per task
Number of CPU cores allocated per task
2
memory_gb
Int
8
Memory allocated in GB for ww-dropletutils, ww-scran, and ww-scater tasks
Memory allocated in GB for ww-dropletutils, ww-scran, and ww-scater tasks
8
singler_memory_gb
Int
16
Memory allocated in GB for ww-singler tasks (higher default since celldex reference loading and clustering need more headroom)
Memory allocated in GB for ww-singler tasks (higher default since celldex reference loading and clustering need more headroom)
16

Outputs

Name
Type
Expression
Description
sce_rds
Array[File]
sample_sce_rds
Array of loaded SingleCellExperiment RDS objects for each sample, prior to QC/normalization
Array of loaded SingleCellExperiment RDS objects for each sample, prior to QC/normalization
sample_sce_rds
empty_drops_csv
Array[File?]
empty_drops_filter.empty_drops_csv
Array of per-barcode emptyDrops statistics for samples provided as a raw matrix (empty for samples provided pre-filtered)
Array of per-barcode emptyDrops statistics for samples provided as a raw matrix (empty for samples provided pre-filtered)
empty_drops_filter.empty_drops_csv
barcode_rank_plot
Array[File?]
empty_drops_filter.barcode_rank_pdf
Array of barcode-rank QC plots for samples provided as a raw matrix (empty for samples provided pre-filtered)
Array of barcode-rank QC plots for samples provided as a raw matrix (empty for samples provided pre-filtered)
empty_drops_filter.barcode_rank_pdf
scran_sce_object
Array[File]
run_scran.sce_object
Array of normalized SingleCellExperiment RDS objects with size factors and PCA for each sample
Array of normalized SingleCellExperiment RDS objects with size factors and PCA for each sample
run_scran.sce_object
scran_qc_plot
Array[File]
run_scran.qc_plot
Array of per-cell QC scatter plots from scran for each sample
Array of per-cell QC scatter plots from scran for each sample
run_scran.qc_plot
scran_size_factor_plot
Array[File]
run_scran.size_factor_plot
Array of size factor histograms for each sample
Array of size factor histograms for each sample
run_scran.size_factor_plot
scran_mean_variance_plot
Array[File]
run_scran.mean_variance_plot
Array of mean-variance trend plots for each sample
Array of mean-variance trend plots for each sample
run_scran.mean_variance_plot
scran_hvg_table
Array[File]
run_scran.hvg_table
Array of CSVs of genes ranked by biological variance for each sample
Array of CSVs of genes ranked by biological variance for each sample
run_scran.hvg_table
scater_sce_object
Array[File]
run_scater.sce_object
Array of SingleCellExperiment RDS objects with PCA and UMAP embeddings for each sample
Array of SingleCellExperiment RDS objects with PCA and UMAP embeddings for each sample
run_scater.sce_object
scater_pca_plot
Array[File]
run_scater.pca_plot
Array of PCA scatter plots for each sample
Array of PCA scatter plots for each sample
run_scater.pca_plot
scater_umap_plot
Array[File]
run_scater.umap_plot
Array of UMAP scatter plots for each sample
Array of UMAP scatter plots for each sample
run_scater.umap_plot
scater_qc_plot
Array[File]
run_scater.qc_plot
Array of per-cell QC scatter plots from scater for each sample
Array of per-cell QC scatter plots from scater for each sample
run_scater.qc_plot
singler_sce_object
Array[File]
run_singler.sce_object
Array of final SingleCellExperiment RDS objects with cluster assignments and predicted cell types for each sample
Array of final SingleCellExperiment RDS objects with cluster assignments and predicted cell types for each sample
run_singler.sce_object
singler_cluster_table
Array[File]
run_singler.cluster_table
Array of CSVs mapping cell barcodes to clusters for each sample
Array of CSVs mapping cell barcodes to clusters for each sample
run_singler.cluster_table
singler_marker_table
Array[File]
run_singler.marker_table
Array of CSVs of top marker genes per cluster for each sample
Array of CSVs of top marker genes per cluster for each sample
run_singler.marker_table
singler_prediction_table
Array[File]
run_singler.prediction_table
Array of CSVs of SingleR cell-type predictions for each sample
Array of CSVs of SingleR cell-type predictions for each sample
run_singler.prediction_table
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Inputs
Required Inputs
Other Inputs
Outputs
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